Aalto University

About: Aalto University is a education organization based out in Espoo, Finland. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 9969 authors who have published 32648 publications receiving 829626 citations. The organization is also known as: TKK & Aalto-korkeakoulu.

Denser than the densest subgraph: extracting optimal quasi-cliques with quality guarantees

Abstract: Finding dense subgraphs is an important graph-mining task with many applications. Given that the direct optimization of edge density is not meaningful, as even a single edge achieves maximum density, research has focused on optimizing alternative density functions. A very popular among such functions is the average degree, whose maximization leads to the well-known densest-subgraph notion. Surprisingly enough, however, densest subgraphs are typically large graphs, with small edge density and large diameter. In this paper, we define a novel density function, which gives subgraphs of much higher quality than densest subgraphs: the graphs found by our method are compact, dense, and with smaller diameter. We show that the proposed function can be derived from a general framework, which includes other important density functions as subcases and for which we show interesting general theoretical properties. To optimize the proposed function we provide an additive approximation algorithm and a local-search heuristic. Both algorithms are very efficient and scale well to large graphs. We evaluate our algorithms on real and synthetic datasets, and we also devise several application studies as variants of our original problem. When compared with the method that finds the subgraph of the largest average degree, our algorithms return denser subgraphs with smaller diameter. Finally, we discuss new interesting research directions that our problem leaves open.

Cooperative Sensing With Imperfect Reporting Channels: Hard Decisions or Soft Decisions?

Abstract: This paper focuses on the performance analysis and comparison of hard decision (HD) and soft decision (SD) based approaches for cooperative spectrum sensing in the presence of reporting channel errors. For cooperative sensing (CS) in cognitive radio networks, a distributed detection approach with displaced sensors and a fusion center (FC) is employed. For HD based CS, each secondary user (SU) sends a one-bit hard local decision to the FC. For SD based CS, each SU sends a quantized version of a local decision statistic such as the log-likelihood ratio or any suitable sufficient statistic. The decision statistics are sent through channels that may cause errors. The effects of channel errors are incorporated in the analysis through the bit error probability (BEP). For HD based CS, the counting rule or the K-out-of-N rule is used at the FC. For SD based CS, the optimal fusion rule in the presence of reporting channel errors is derived and its distribution is established. A comparison of the two schemes is conducted to show that there is a performance gain in using SD based CS even in the presence of reporting channel errors. In addition, a BEP wall is shown to exist for CS such that if the BEP is above a certain value, then irrespective of the received signal strength corresponding to the primary user, the constraints on false alarm probability and detection probability cannot be met. It is shown that the performance of HD based CS is very sensitive to the BEP wall phenomenon while the SD based CS is more robust in that sense.

Black phosphorus ink formulation for inkjet printing of optoelectronics and photonics

Abstract: Black phosphorus is a two-dimensional material of great interest, in part because of its high carrier mobility and thickness dependent direct bandgap. However, its instability under ambient conditions limits material deposition options for device fabrication. Here we show a black phosphorus ink that can be reliably inkjet printed, enabling scalable development of optoelectronic and photonic devices. Our binder-free ink suppresses coffee ring formation through induced recirculating Marangoni flow, and supports excellent consistency ( 30 days) oxidation. We demonstrate printed black phosphorus as a passive switch for ultrafast lasers, stable against intense irradiation, and as a visible to near-infrared photodetector with high responsivities. Our work highlights the promise of this material as a functional ink platform for printed devices. Atomically thin black phosphorus shows promise for optoelectronics and photonics, yet its instability under environmental conditions and the lack of well-established large-area synthesis protocols hinder its applications. Here, the authors demonstrate a stable black phosphorus ink suitable for printed ultrafast lasers and photodetectors.

A fast method to produce strong NFC films as a platform for barrier and functional materials.

Abstract: In this study, we present a rapid method to prepare robust, solvent-resistant, nanofibrillated cellulose (NFC) films that can be further surface-modified for functionality. The oxygen, water vapor, and grease barrier properties of the films were measured, and in addition, mechanical properties in the dry and wet state and solvent resistance were evaluated. The pure unmodified NFC films were good barriers for oxygen gas and grease. At a relative humidity below 65%, oxygen permeability of the pure and unmodified NFC films was below 0.6 cm3 μm m–2 d–1 kPa–1, and no grease penetrated the film. However, the largest advantage of these films was their resistance to various solvents, such as water, methanol, toluene, and dimethylacetamide. Although they absorbed a substantial amount of solvent, the films could still be handled after 24 h of solvent soaking. Hot-pressing was introduced as a convenient method to not only increase the drying speed of the films but also enhance the robustness of the films. The wet st...